Jaeger vs Grafana Tempo
tracing backend — standalone CNCF vs. Grafana-stack object-storage-native
| Jaeger | Grafana Tempo | |
|---|---|---|
| Summary | The CNCF graduated distributed tracing system, originally from Uber. The default open-source choice for traces. | High-scale distributed tracing backend. Stores traces in cheap object storage (S3, GCS). |
| License | Apache-2.0 | AGPL-3.0 |
| Language | Go | Go |
| GitHub stars (approx) | 23000 | 4300 |
| Categories | traces | traces |
| Replaces SaaS | datadog, new-relic, honeycomb | datadog, honeycomb, new-relic |
| Self-host deployment | docker, kubernetes (jaeger-operator) | docker, kubernetes helm |
| Commercial hosted option | no / self-host only | yes (vendor-run) |
| Repository | https://github.com/jaegertracing/jaeger | https://github.com/grafana/tempo |
| Freshness checked | 2026-05-17 | 2026-04-22 |
When to prefer Jaeger
You want a standalone tracing UI and storage system that doesn't assume Grafana. Jaeger ships its own query UI, supports trace search and filtering natively, and works well as a self-contained observability tool.
When to prefer Grafana Tempo
You already run Grafana plus Loki plus Prometheus and want traces in the same stack with the same object-storage cost profile. Tempo is search-by-trace-ID first (no rich indexing) which keeps storage cheap, and the Grafana UI integrates it tightly with logs and metrics.